In living cells, complex processes are typically accomplished by highly specific binding interactions among functional cell components, most commonly involving one or more proteins. Understanding which proteins bind to one another, and under what circumstances, poses difficult unsolved problems. An approach to learning which proteins bind to each other to form protein complexes is to isolate functional protein complexes, or portions thereof, in order to identify their components.
However, the dynamic nature of cellular machineries is frequently built on transient and/or weak protein associations. Those low affinity interactions preclude stringent methods for the isolation and identification of protein networks around a protein of interest. In fact, most in vivo protein-protein binding is transient and occurs only briefly to facilitate signaling or metabolic function. Capturing or freezing those momentary contacts to study which proteins are involved and how they interact is difficult.
For example, following single virus particles during an initial phase of infection, that is, virus entry into target cells, can reveal crucial information on the mechanism of pathogen infections and likewise cellular transport and membrane dynamics. A problem with studying viral entrance pathways is that virus entry is highly dynamic. The subsequent interactions of the virus with cellular structures during the various entry steps (binding, plasma membrane dynamics, internalization/endocytosis, intracellular trafficking, penetration/membrane fusion) are transient, and they require motion of the virion. Additionally, the virus interacts with cellular structures that are dynamic themselves.
An approach that has been used to study viral entry is to optically label virus particles and then follow the particles in real time as they infect a cell. However, several challenges are associated with the analysis of viral entry in live cells using optically labeled viral particles. Practical challenges lie within the detection noise of the sample, that is, how reliably viral particles or cellular structures can be discerned from background noise. Additionally, in the infective processes, particularly quick, transient events, are not synchronized. Different virions within a population may follow different itineraries at the time of acquisition. Alternatively, a single virus may exhibit several different types of motion during the time of data acquisition such as diffusion, directed motion, confinement (on the plasma membrane) followed by fast long range intracellular movement. In addition, the ratios of overall virus particles to infectious particles can be high, and this may make it difficult to define the relevant motion patterns of infectious particles as opposed to the biological noise of noninfectious particles.